Tutorials

Abstract

The conventional application of ultrasound in the medical field is in tissue imaging. Over the past decade or so, ultrasound has increasingly found interesting applications in neuromodulation of neural activity as well as wireless power transfer to deeply implanted miniature (millimeter scale and smaller) medical devices. Although ultrasound is relatively a new modality for neuromodulation, several research groups across the globe have demonstrated on both animals and humans that ultrasound has a robust and safe effect on neural tissue for both activation and suppression of neural activity. Also, ultrasonic wireless power transfer to millimeter-scale implants have successfully been demonstrated in different applications, such as neural recording and stimulation. Both ultrasound neuromodulation and wireless power transfer applications still require significant amount of research and development in ultrasonic transducers, ultrasonic arrays, CMOS circuits (particularly high-voltage beamforming drivers), biomedical system integration, and in vivo validations, all of which are of great interest to the biomedical circuits and systems (BioCAS) community. In this tutorial, I will present the basics, recent developments, challenges, and applications of ultrasound neuromodulation and ultrasound wireless power transfer to millimeter-scale implants.

Biography

Mehdi Kiani received his Ph.D. degree in Electrical and Computer Engineering from the Georgia Institute of Technology in 2014. He joined the faculty of the School of Electrical Engineering and Computer Science at the Pennsylvania State University in August 2014 where he is currently an Associate Professor. His research interests are in the multidisciplinary areas of analog and power-management integrated circuits, ultrasound-based medical systems, wireless implantable medical devices, and neural interfaces. He was a recipient of the 2020 NSF CAREER Award. He is currently an Associate Editor of the IEEE Transactions on Biomedical Circuits and Systems and IEEE Transactions on Biomedical Engineering. He serves as the technical program committee member of the IEEE International Solid-State Circuits Conference in the IMMD subcommittee.

Abstract

Inspection, palpation, percussion, and auscultation (IPPA) are the four key physical assessments to understand the condition of a patient. In particular, adventitious heart and respiratory sounds can be heard by performing auscultation on the anterior and posterior chest. However, auscultation requires a lot of experience to be able to determine the types of sounds heard. Furthermore, the inter-listener variability among physicians and the lack of quantitative measurements make lung auscultation a subjective process. Therefore, the digital stethoscope has been gradually adopted in several hospitals to provide digital recording, which can be used for further analysis. My tutorial will begin with an introduction to the auscultation of our cardiac and respiratory systems, followed by a discussion of heart and lung sounds. On this basis, we will review the different features of the digital stethoscope system and discuss how signal processing, machine learning, and deep learning models can improve the detection and classification of heart and respiratory sounds. Furthermore, in alignment with the BioCAS student design contest, we hope to encourage more people to be engaged in this meaningful research topic.

Biography

Yongfu Li (S’09–M’14-SM’18) received the B.Eng. and Ph.D. degrees from the Department of Electrical and Computing Engineering, National University of Singapore (NUS), Singapore.

He is currently an Associate Professor with the Department of Micro and Nano Electronics Engineering and MoE Key Lab of Artificial Intelligence, Shanghai Jiao Tong University, China. He was a research engineer with NUS, from 2013 to 2014. He was a senior engineer (2014-2016), principal engineer (2016-2018) and member of technical staff (2018-2019) with GLOBALFOUNDRIES, as a Design-to-Manufacturing (DFM) Computer-Aided Design (CAD) research and development engineer. His research interests include analog/mixed signal circuits, data converters, power converters, biomedical signal processing with deep learning technique and DFM circuit automation.

Abstract

Technology has significantly impacted the capabilities of medical diagnostics and treatment, however only a fraction of the research conducted in the biomedical technology domain makes it to the market. The reason for this is because the process of developing and marketing novel medical devices is extremely complex and laden with many pitfalls. This tutorial aims to provide a brief overview of the issues that academics or researchers will face if they decide to embark on the long journey of taking their invention to market. The basic requirements of any product going to market is that the device provides a value proposition to the customer and that the company providing the product is economically viable. Thus this journey starts with understanding if there really is a business case and formulating a strategy for protecting the intellectual property early on. The options for exploiting the technology vary from licensing to becoming an academic entrepreneur through a startup company. This tutorial will focus on the startup route, where the academic will be closely involved with the founding and running of the company. Considerations to be taken into account are the structure of the startup, choosing a team and defining their roles, formulating a funding strategy, selecting a beachhead market and testing the various assumptions on a regular basis. Medical device companies have extra hurdles to overcome, which include that of acquiring regulatory approvals and that of designing and implementing a Quality Management System. In view of this, transitioning from an academic prototype to a product is not trivial. The final part of the tutorial will cover the basics of going to market, including postmarket surveillance, which is usually a legal requirement of medical device companies, to ensure the safety of the end users.

Biography

Julius Georgiou (IEEE M’98-SM’08) is an Associate Professor at the University of Cyprus. He received his M.Eng degree in Electrical and Electronic Engineering and Ph.D. degree from Imperial College London in 1998 and 2003 respectively. For two years he worked as Head of Micropower Design in a technology start-up company, Toumaz Technology. In 2004 he joined the Johns Hopkins University as a Postdoctoral Fellow, before becoming a faculty member at the University of Cyprus from 2005 onwards. In parallel, he has been involved in the founding of multiple medical device startup companies, based on patents stemming from his research.

Prof. Georgiou is a member of the IEEE Circuits and Systems Society, was the Chair of the IEEE Biomedical and Life Science Circuits and Systems (BioCAS) Technical Committee, as well as a member of the IEEE Circuits and Systems Society Analog Signal Processing Technical Committee. He served as the General Chair of the 2010 IEEE Biomedical Circuits and Systems Conference and is the Action Chair of the EU COST Action ICT-1401 on “Memristors-Devices, Models, Circuits, Systems and Applications - MemoCIS”. Prof. Georgiou was an IEEE Circuits and Systems Society Distinguished Lecturer for 2016-2017. He is also is an Associate Editor of the IEEE Transactions on Biomedical Circuits and Systems and Associate Editor of the Frontiers in Neuromorphic Engineering Journal. He is a recipient of a best paper award at the IEEE ISCAS 2011 International Symposium and at the IEEE BioDevices 2008 Conference. In 2016 he received the 2015 ONE Award from the President of the Republic of Cyprus for his research accomplishments.

His research interests include Low-power analog and digital ASICs, implantable biomedical devices, bioinspired electronic systems, ElectroUteroGraph hardware, ElectroUteroGram signal processing, electronics for space, brain-computer-interfaces (BCIs), memristive devices, inertial and optical sensors and related systems.

Abstract

Biological processes such as neuronal signaling and cell growth are among the most complex micro- and nano-scale processes in nature. Historically such processes have been studied at system level because there were no tools available to study individual components of the process. However, cellular-level interfacing is needed to provide better understanding of the brain and to develop more advanced prosthetic devices and brain-machine interfaces. With semiconductor technology innovations, much recent work has been focused on unraveling biological complexity, but also on driving new diagnoses, treatments and therapies that are tailored to the individual. One of the drivers behind those innovations is novel CMOS circuits enabling multi-modal, high-precision data collection and analysis at ultra-low power consumption. In this talk, I will present recent biomedical developments based on silicon technology, and I will discuss the requirements, materials, circuit techniques and design challenges of their ASIC and SoC platforms.

Biography

Carolina Mora Lopez received her Ph.D. degree in Electrical Engineering in 2012 from the KU Leuven, Belgium, in collaboration with imec, Belgium. From 2012 to 2018, she worked at imec as a researcher and analog designer focused on interfaces for neural-sensing applications. During this time, she was the lead analog designer and project leader of the Neuropixels development project which resulted in the conception and fabrication of the Neuropixels 1.0 and 2.0 neural probes. She is currently the principal scientist and team leader of the Circuits & Systems for Neural Interfaces team at imec, which develops circuits and technologies for electrophysiology, neuroprosthetics and BMI. Her research interests include analog and mixed-signal circuit design for sensor, bioelectronic and neural interfaces. Carolina is a senior IEEE member and serves on the technical program committee of the ISSC conference, ISSCC SRP, VLSI circuits symposium, and ESSCIRC conference.